Evaluating Urban Data Models for Parking Regulation Compliance: A Requirement-Driven Approach

Abstract

Parking facilities play a vital role in urban planning and traffic management. However, regulatory assessments remain largely manual, building-centric, and focused on the initial lifecycle phase, with limited support for operational parking facilities or city-scale analysis. This study identifies legal and technical requirements from the Bavarian Garage and Parking Space Ordinance (GaStellV) and technical design standards for ramps, driveways, and pedestrian paths, and formalises them into a UML-based regulatory conceptual model for automated compliance checking. Representative urban data models, including CityGML, IFC, OpenDRIVE, and XPlanung, are then evaluated based on their ability to represent the identified regulatory concepts, considering semantic representation, and geometric as well as topological modelling capabilities. The evaluation shows that while each model excels within its application domain, none independently represents the complete set of regulatory requirements. Among the evaluated standards, CityGML 3.0 provides the most comprehensive foundation for city-scale automated compliance checking. Consequently, the regulatory conceptual model is mapped to and extends the CityGML 3.0 conceptual model using generic attributes together with the Building and Transportation modules. The approach demonstrates the feasibility of automatic, semantic, city-scale parking regulation checking.